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The Daily Economic Indicator: tracking economic activity daily during the lockdown

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  • Lourenço, Nuno
  • Rua, António

Abstract

The SARS-CoV-2 outbreak made clear the urgent need to depart from traditional statistics, typically released with a lag and available at a relatively low frequency. This led to unparalleled efforts to put forward high-frequency indicators to track economic developments timely. By resorting to non-traditional data sources, we propose a novel daily economic indicator to track economic activity in Portugal. It corresponds to the latent variable of a set of daily series within a factor model framework. We find a sudden and sharp drop in economic activity in mid-March 2020, when the lockdown of several activities was declared due to the COVID-19 pandemic. Since in this approach we address the complexities of high-frequency data without further smoothing, we are able to identify sudden changes of economic activity in a timely and daily manner in contrast with other approaches.

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  • Lourenço, Nuno & Rua, António, 2021. "The Daily Economic Indicator: tracking economic activity daily during the lockdown," Economic Modelling, Elsevier, vol. 100(C).
    • Handle: RePEc:eee:ecmode:v:100:y:2021:i:c:s0264999321000894
    DOI: 10.1016/j.econmod.2021.105500
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    6. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
    7. Cristina Manteu & Sara Serra & Sónia Cabral & Cátia Silva, 2021. "Consumption expenditure during the COVID-19 pandemic: an analysis based on Portuguese card transaction data," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    8. Marco Fruzzetti & Tiziano Ropele, 2024. "Nowcasting Italian industrial production: the predictive role of lubricant oils," Questioni di Economia e Finanza (Occasional Papers) 866, Bank of Italy, Economic Research and International Relations Area.
    9. Robert Lehmann & Sascha Möhrle, 2022. "Forecasting Regional Industrial Production with High-Frequency Electricity Consumption Data," CESifo Working Paper Series 9917, CESifo.
    10. Zhang, Dongyang & Zheng, Wenping, 2022. "Does COVID-19 make the firms’ performance worse? Evidence from the Chinese listed companies," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 560-570.
    11. Mantas Lukauskas & Vaida Pilinkienė & Jurgita Bruneckienė & Alina Stundžienė & Andrius Grybauskas & Tomas Ruzgas, 2022. "Economic Activity Forecasting Based on the Sentiment Analysis of News," Mathematics, MDPI, vol. 10(19), pages 1-22, September.
    12. AlQershi, Nagwan & Saufi, Roselina Binti Ahmad & Ismail, Noor Azizi & Mohamad, Mohd Rosli Bin & Ramayah, T. & Muhammad, Nik Maheran Nik & Yusoff, Mohd Nor Hakimin Bin, 2023. "The moderating role of market turbulence beyond the Covid-19 pandemic and Russia-Ukraine crisis on the relationship between intellectual capital and business sustainability," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    13. Stankov, Petar, 2024. "Will voters polarize over pandemic restrictions? Theory and evidence from COVID-19," Economic Modelling, Elsevier, vol. 136(C).
    14. António Rua & Nuno Lourenço, 2022. "A circular business cycle clock for Portugal," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    15. Ollech, Daniel, 2021. "Economic analysis using higher frequency time series: Challenges for seasonal adjustment," Discussion Papers 53/2021, Deutsche Bundesbank.
    16. Juan Pablo Cote-Barón & Karen L. Pulido-Mahecha & Nicol Valeria Rodríguez-Rodríguez & Carlos D. Rojas-Martínez, 2023. "El ISAE: Un Indicador para Monitorear la Actividad Económica Colombiana en Alta Frecuencia," Borradores de Economia 1225, Banco de la Republica de Colombia.
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    More about this item

    Keywords

    Daily economic index; High-frequency; Measurement of economic activity; Factor model; COVID-19;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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